Audio Visual Emotion Recognition For Natural Human Robot Interaction
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Audio Visual Emotion Recognition For Natural Human Robot Interaction
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Author : Ahmad Rabie
language : en
Publisher:
Release Date : 2011
Audio Visual Emotion Recognition For Natural Human Robot Interaction written by Ahmad Rabie and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
Robot Behavior Generation And Human Behavior Understanding In Natural Human Robot Interaction
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Author : Chuang Yu
language : en
Publisher:
Release Date : 2021
Robot Behavior Generation And Human Behavior Understanding In Natural Human Robot Interaction written by Chuang Yu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
Having a natural interaction makes a significant difference in a successful human-robot interaction (HRI). The natural HRI refers to both human multimodal behavior understanding and robot verbal or non-verbal behavior generation. Humans can naturally communicate through spoken dialogue and non-verbal behaviors. Hence, a robot should perceive and understand human behaviors so as to be capable of producing a natural multimodal and spontaneous behavior that matches the social context. In this thesis, we explore human behavior understanding and robot behavior generation for natural HRI. This includes multimodal human emotion recognition with visual information extracted from RGB-D and thermal cameras and non-verbal multimodal robot behavior synthesis.Emotion recognition based on multimodal human behaviors during HRI can help robots understand user states and exhibit a natural social interaction. In this thesis, we explored multimodal emotion recognition with thermal facial information and 3D gait data in HRI scene when the emotion cues from thermal face and gait data are difficult to disguise. A multimodal database with thermal face images and 3D gait data was built through the HRI experiments. We tested the various unimodal emotion classifiers (i.e., CNN, HMM, Random Forest model, SVM) and one decision-based hybrid emotion classifier on the database for offline emotion recognition. We also explored an online emotion recognition system with limited capability in the real-time HRI setting. Interaction plays a critical role in skills learning for natural communication. Robots can get feedback during the interaction to improve their social abilities in HRI.To improve our online emotion recognition system, we developed an interactive robot learning (IRL) model with the human in the loop. The IRL model can apply the human verbal feedback to label or relabel the data for retraining the emotion recognition model in a long-term interaction situation. After using the interactive robot learning model, the robot could obtain a better emotion recognition accuracy in real-time HRI.The human non-verbal behaviors such as gestures and face action occur spontaneously with speech, which leads to a natural and expressive interaction. Speech-driven gesture and face action generation are vital to enable a social robot to exhibit social cues and conduct a successful HRI. This thesis proposes a new temporal GAN (Generative Adversarial Network) architecture for a one-to-many mapping from acoustic speech representation to the humanoid robot's corresponding gestures. We also developed an audio-visual database to train the speaking gesture generation model. The database includes the speech audio data extracted directly from the videos and the associated 3D human pose data extracted from 2D RGB images. The generated gestures from the trained co-speech gesture synthesizer can be applied to social robots with arms. The evaluation result shows the effectiveness of our generative model for speech-driven robot gesture generation. Moreover, we developed an effective speech-driven facial action synthesizer based on GAN, i.e., given an acoustic speech, a synchronous and realistic 3D facial action sequence is generated. A mapping between the 3D human facial actions to real robot facial actions that regulate the Zeno robot facial expression is completed. The application of co-speech non-verbal robot behaviors (gesture and face action) synthesis for the social robot can make a friendly and natural human-robot interaction.
Emotion Recognition And Understanding For Emotional Human Robot Interaction Systems
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Author : Luefeng Chen
language : en
Publisher: Springer Nature
Release Date : 2020-11-13
Emotion Recognition And Understanding For Emotional Human Robot Interaction Systems written by Luefeng Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-13 with Technology & Engineering categories.
This book focuses on the key technologies and scientific problems involved in emotional robot systems, such as multimodal emotion recognition (i.e., facial expression/speech/gesture and their multimodal emotion recognition) and emotion intention understanding, and presents the design and application examples of emotional HRI systems. Aiming at the development needs of emotional robots and emotional human–robot interaction (HRI) systems, this book introduces basic concepts, system architecture, and system functions of affective computing and emotional robot systems. With the professionalism of this book, it serves as a useful reference for engineers in affective computing, and graduate students interested in emotion recognition and intention understanding. This book offers the latest approaches to this active research area. It provides readers with the state-of-the-art methods of multimodal emotion recognition, intention understanding, and application examples of emotional HRI systems.
Deep Learning Techniques Applied To Affective Computing
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Author : Zhen Cui
language : en
Publisher: Frontiers Media SA
Release Date : 2023-06-14
Deep Learning Techniques Applied To Affective Computing written by Zhen Cui and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-14 with Science categories.
Affective computing refers to computing that relates to, arises from, or influences emotions. The goal of affective computing is to bridge the gap between humans and machines and ultimately endow machines with emotional intelligence for improving natural human-machine interaction. In the context of human-robot interaction (HRI), it is hoped that robots can be endowed with human-like capabilities of observation, interpretation, and emotional expression. The research on affective computing has recently achieved extensive progress with many fields contributing including neuroscience, psychology, education, medicine, behavior, sociology, and computer science. Current research in affective computing concentrates on estimating human emotions through different forms of signals such as speech, face, text, EEG, fMRI, and many others. In neuroscience, the neural mechanisms of emotion are explored by combining neuroscience with the psychological study of personality, emotion, and mood. In psychology and philosophy, emotion typically includes a subjective, conscious experience characterized primarily by psychophysiological expressions, biological reactions, and mental states. The multi-disciplinary features of understanding “emotion” result in the fact that inferring the emotion of humans is definitely difficult. As a result, a multi-disciplinary approach is required to facilitate the development of affective computing. One of the challenging problems in affective computing is the affective gap, i.e., the inconsistency between the extracted feature representations and subjective emotions. To bridge the affective gap, various hand-crafted features have been widely employed to characterize subjective emotions. However, these hand-crafted features are usually low-level, and they may hence not be discriminative enough to depict subjective emotions. To address this issue, the recently-emerged deep learning (also called deep neural networks) techniques provide a possible solution. Due to the used multi-layer network structure, deep learning techniques are capable of learning high-level contributing features from a large dataset and have exhibited excellent performance in multiple application domains such as computer vision, signal processing, natural language processing, human-computer interaction, and so on. The goal of this Research Topic is to gather novel contributions on deep learning techniques applied to affective computing across the diverse fields of psychology, machine learning, neuroscience, education, behavior, sociology, and computer science to converge with those active in other research areas, such as speech emotion recognition, facial expression recognition, Electroencephalogram (EEG) based emotion estimation, human physiological signal (heart rate) estimation, affective human-robot interaction, multimodal affective computing, etc. We welcome researchers to contribute their original papers as well as review articles to provide works regarding the neural approach from computation to affective computing systems. This Research Topic aims to bring together research including, but not limited to: • Deep learning architectures and algorithms for affective computing tasks such as emotion recognition from speech, face, text, EEG, fMRI, and many others. • Explainability of deep Learning algorithms for affective computing. • Multi-task learning techniques for emotion, personality and depression detection, etc. • Novel datasets for affective computing • Applications of affective computing in robots, such as emotion-aware human-robot interaction and social robots, etc.
Context Aware Human Robot And Human Agent Interaction
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Author : Nadia Magnenat-Thalmann
language : en
Publisher: Springer
Release Date : 2015-09-25
Context Aware Human Robot And Human Agent Interaction written by Nadia Magnenat-Thalmann and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-25 with Computers categories.
This is the first book to describe how Autonomous Virtual Humans and Social Robots can interact with real people, be aware of the environment around them, and react to various situations. Researchers from around the world present the main techniques for tracking and analysing humans and their behaviour and contemplate the potential for these virtual humans and robots to replace or stand in for their human counterparts, tackling areas such as awareness and reactions to real world stimuli and using the same modalities as humans do: verbal and body gestures, facial expressions and gaze to aid seamless human-computer interaction (HCI). The research presented in this volume is split into three sections: ·User Understanding through Multisensory Perception: deals with the analysis and recognition of a given situation or stimuli, addressing issues of facial recognition, body gestures and sound localization. ·Facial and Body Modelling Animation: presents the methods used in modelling and animating faces and bodies to generate realistic motion. ·Modelling Human Behaviours: presents the behavioural aspects of virtual humans and social robots when interacting and reacting to real humans and each other. Context Aware Human-Robot and Human-Agent Interaction would be of great use to students, academics and industry specialists in areas like Robotics, HCI, and Computer Graphics.
Emotional Design In Human Robot Interaction
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Author : Hande Ayanoğlu
language : en
Publisher: Springer Nature
Release Date : 2019-09-09
Emotional Design In Human Robot Interaction written by Hande Ayanoğlu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-09 with Computers categories.
While social robots participation increases in everyday human life, their presence in diverse contexts and situations is expected. At the same point, users tend to become more demanding regarding their roles, abilities, behaviour and appearance. Thus, designers and developers are confronted with the need to design more sophisticated robots that can produce such a positive reaction from users so as to become well accepted in various cases of use. Like this, Human-Robot Interaction has become a developing area. Emotions are an important part in human life, since they mediate the interaction with other humans, entities and/or products. In recent years, there has been an increase in the importance of emotions applied to the design field, giving rise to the so-called Emotional Design area. In the case of Human-Robot Interaction, the emotional design can help to elicit (e.g., pleasurable) or prevent (e.g., unpleasant) emotional/affective reactions/responses. This book gives a practical introduction to emotional design in human-robot interaction and supports designers with knowledge and research tools to help them take design decisions based on a User-Centred Design approach. It should also be useful to people interested in design processes, even if not directly related to the design of social robots but, instead, to other technology-based artefacts. The text is meant as a reference source with practical guidelines and advice for design issues.
Multi Modal Emotion Recognition For Human Robot Interaction
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Author : 李尚庭
language : en
Publisher:
Release Date : 2016
Multi Modal Emotion Recognition For Human Robot Interaction written by 李尚庭 and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
Handbook Of Research On Synthesizing Human Emotion In Intelligent Systems And Robotics
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Author : Vallverdú, Jordi
language : en
Publisher: IGI Global
Release Date : 2014-11-30
Handbook Of Research On Synthesizing Human Emotion In Intelligent Systems And Robotics written by Vallverdú, Jordi and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-30 with Computers categories.
Emotions convey significant information through means of natural language analysis, embodiment, and emotional signing. Machines equipped with the ability to experience and interpret emotions perform better in complex environments and share in the emotionally-rich social context. The Handbook of Research on Synthesizing Human Emotion in Intelligent Systems and Robotics presents a solid framework for taking human-robot interaction closer to its full potential. Presenting a close look at all the factors involved in modeling emotions and applying a thorough understanding of human emotional recognition to technology, this volume appeals to active researchers in the fields of artificial emotions, artificial intelligence, computing, robotics, philosophy, and psychology, as well as to students interested in the research of synthetic emotions.
Emotion Recognition Through Body Language For Human Robot Interaction
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Author : Lilita Kiforenko
language : en
Publisher:
Release Date : 2013
Emotion Recognition Through Body Language For Human Robot Interaction written by Lilita Kiforenko and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.
A Facial Expression Imitation System For The Primitive Of Intuitive Human Robot Interaction
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Author : Do Hyoung Kim
language : en
Publisher:
Release Date : 2007
A Facial Expression Imitation System For The Primitive Of Intuitive Human Robot Interaction written by Do Hyoung Kim and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.
This Chapter has attempted to deal with the issues on establishing a facial expression imitation system for natural and intuitive interactions with humans. Several real-time cognition abilities are implemented to a robotic system such as face detection, face tracking, and facial expression recognition. Moreover, a robotic system with facial components is developed, which is able to imitate human's facial expressions. A method of recognizing facial expressions is proposed through the use of an innovative rectangle feature. Using the AdaBoost algorithm, an expanded version of Viola and Jones' method has been suggested as a new approach. We deal with 7 facial expressions: neutral, happiness, anger, sadness, surprise, disgust, and fear. For each facial expression, we found five suitable rectangle features using the AdaBoost learning algorithm. These 35 rectangle features and 7 rectangle features were used to find new weak classifiers for facial expression recognition. A real-time performance rate can be achieved through constructing the strong classifier while extracting a few efficient weak classifiers by AdaBoost learning. In addition, an active vision system for social interaction with humans is developed. We proposed a high-speed bell-shaped velocity profiler to reduce the magnitude of jerking motion and used this method to control 12 actuators in real-time. We proved our distributed control structure and the proposed fast bell-shaped velocity profiler to be practical. Several basic algorithms, face detection and tracking, are implemented on the developed system. By directing the robot's gaze to the visual target, the person interacting with the robot can accurately use the robot's gaze as an indicator of what the robot is attending to. This greatly facilitates the interpretation and readability of the robot's behavior, as the robot reacts specifically to the thing that it is looking at. In order to implement visual attention, the basic functionality mentioned above, e.g. face detection, tracking and motor control, is needed. Finally, we introduced an artificial facial expression imitation system using a robot head. There are a number of real-time issues for developing the robotic system. In this Chapter, one solution for developing it is addressed. Our final goal of this research is that humans can easily perceive motor actions semantically and intuitively, regardless of what the robot intends. However, our research lacks a sound understanding of natural and intuitive social interactions among humans. Our future research will focus on perceiving the mental model of human to apply it to the robotic system. It is expected that the suitable mental model for the robots will convey robot's emotion by facial expressions.